Articles Burden of enteric fever at three urban sites in Africa and Asia: a multicentre population-based study

Abstract

Background
Enteric fever is a serious public health concern in many low-income and middle-income countries. Numerous data gaps exist concerning the epidemiology of Salmonella enterica serotype Typhi (S Typhi) and Salmonella enterica serotype Paratyphi (S Paratyphi), which are the causative agents of enteric fever. We aimed to determine the burden of enteric fever in three urban sites in Africa and Asia.

Methods
In this multicentre population-based study, we did a demographic census at three urban sites in Africa (Blantyre, Malawi) and Asia (Kathmandu, Nepal and Dhaka, Bangladesh) between June 1, 2016, and Sept 25, 2018. Households were selected randomly from the demographic census. Participants from within the geographical census area presenting to study health-care facilities were approached for recruitment if they had a history of fever for 72 h or more (later changed to >48 h) or temperature of 38·0°C or higher. Facility-based passive surveillance was done between Nov 11, 2016, and Dec 31, 2018, with blood-culture collection for febrile illness. We also did a community-based serological survey to obtain data on Vi-antibody defined infections. We calculated crude incidence for blood-culture-confirmed S Typhi and S Paratyphi infection, and calculated adjusted incidence and seroincidence of S Typhi blood-culture-confirmed infection.

Findings
423 618 individuals were included in the demographic census, contributing 626 219 person-years of observation for febrile illness surveillance. 624 S Typhi and 108 S Paratyphi A isolates were collected from the blood of 12 082 febrile patients. Multidrug resistance was observed in 44% S Typhi isolates and fluoroquinolone resistance in 61% of S Typhi isolates. In Blantyre, the overall crude incidence of blood-culture confirmed S Typhi was 58 cases per 100 000 person-years of observation (95% CI 48–70); the adjusted incidence was 444 cases per 100 000 person-years of observation (95% credible interval [CrI] 347–717). The corresponding rates were 74 (95% CI 62–87) and 1062 (95% CrI 683–1839) in Kathmandu, and 161 (95% CI 145–179) and 1135 (95% CrI 898–1480) in Dhaka. S Paratyphi was not found in Blantyre; overall crude incidence of blood-culture-confirmed S Paratyphi A infection was 6 cases per 100 000 person-years of observation (95% CI 3–11) in Kathmandu and 42 (95% CI 34–52) in Dhaka. Seroconversion rates for S Typhi infection per 100 000 person-years estimated from anti-Vi seroconversion episodes in serological surveillance were 2505 episodes (95% CI 1605–3727) in Blantyre, 7631 (95% CI 5913–9691) in Kathmandu, and 3256 (95% CI 2432–4270) in Dhaka.

Interpretation
High disease incidence and rates of antimicrobial resistance were observed across three different transmission settings and thus necessitate multiple intervention strategies to achieve global control of these pathogens.

Funding
Wellcome Trust and the Bill & Melinda Gates Foundation.

Full text

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e1688
Burden of enteric fever at three urban sites in Africa and Asia:
a multicentre population-based study
James E Meiring*, Mila Shakya*, Farhana Khanam*, Merryn Voysey, Maile T Phillips, Susan Tonks, Deus Thindwa, Thomas C Darton,
Sabina Dongol, Abilasha Karkey, K Zaman, Stephen Baker, Christiane Dolecek, Sarah J Dunstan, Gordon Dougan, Kathryn E Holt,
Robert S Heyderman, Firdausi Qadri, Virginia E Pitzer†, Buddha Basnyat†, Melita A Gordon†, John Clemens†, Andrew J Pollard†, on behalf of the
STRATAA Study Group
Summary
Background Enteric fever is a serious public health concern in many low-income and middle-income countries.
Numerous data gaps exist concerning the epidemiology of Salmonella enterica serotype Typhi (S Typhi) and
Salmonella enterica serotype Paratyphi (S Paratyphi), which are the causative agents of enteric fever. We aimed to
determine the burden of enteric fever in three urban sites in Africa and Asia.
Methods In this multicentre population-based study, we did a demographic census at three urban sites in Africa
(Blantyre, Malawi) and Asia (Kathmandu, Nepal and Dhaka, Bangladesh) between June 1, 2016, and Sept 25, 2018.
Households were selected randomly from the demographic census. Participants from within the geographical census
area presenting to study health-care facilities were approached for recruitment if they had a history of fever for 72 h
or more (later changed to >48 h) or temperature of 38·0°C or higher. Facility-based passive surveillance was done
between Nov 11, 2016, and Dec 31, 2018, with blood-culture collection for febrile illness. We also did a community-
based serological survey to obtain data on Vi-antibody defined infections. We calculated crude incidence for blood-
culture-confirmed S Typhi and S Paratyphi infection, and calculated adjusted incidence and seroincidence of S Typhi
blood-culture-confirmed infection.
Findings 423 618 individuals were included in the demographic census, contributing 626 219 person-years of observation
for febrile illness surveillance. 624 S Typhi and 108 S Paratyphi A isolates were collected from the blood of 12 082 febrile
patients. Multidrug resistance was observed in 44% S Typhi isolates and fluoroquinolone resistance in 61% of S Typhi
isolates. In Blantyre, the overall crude incidence of blood-culture confirmed S Typhi was 58 cases per 100 000 person-
years of observation (95% CI 48–70); the adjusted incidence was 444 cases per 100 000 person-years of observation
(95% credible interval [CrI] 347–717). The corresponding rates were 74 (95% CI 62–87) and 1062 (95% CrI 683–1839) in
Kathmandu, and 161 (95% CI 145–179) and 1135 (95% CrI 898–1480) in Dhaka. S Paratyphi was not found in Blantyre;
overall crude incidence of blood-culture-confirmed S Paratyphi A infection was 6 cases per 100 000 person-years of
observation (95% CI 3–11) in Kathmandu and 42 (95% CI 34–52) in Dhaka. Seroconversion rates for S Typhi infection
per 100 000 person-years estimated from anti-Vi seroconversion episodes in serological surveillance were 2505 episodes
(95% CI 1605–3727) in Blantyre, 7631 (95% CI 5913–9691) in Kathmandu, and 3256 (95% CI 2432–4270) in Dhaka.
Interpretation High disease incidence and rates of antimicrobial resistance were observed across three dierent
transmission settings and thus necessitate multiple intervention strategies to achieve global control of these pathogens.
Funding Wellcome Trust and the Bill & Melinda Gates Foundation.
Copyright © 2021 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.
Introduction
Enteric fever is estimated to cause 11–18 million infections
and 100 000–200 000 deaths globally each year, resulting in
a considerable public health burden in many low-income
and middle-income countries in Africa and Asia.1,2 The
human-restricted pathogens Salmonella enterica serovars
Typhi (S Typhi) and Paratyphi A, B, and C cause enteric
fever, which presents as a non-specific febrile illness after
the oral ingestion of contaminated food or water, with a
reported case fatality rate of around 2·5% despite
antimicrobial treatment.3 High rates of disease have
consistently been reported at urban sites in Asia,4 with an
increasing proportion of S Paratyphi A in some sites.5 In
Africa, the cross-continental introduction of the H58
pathovar from Asia has coincided with a documented
increase in cases of S Typhi, often associated with large
outbreaks, persisting for years, at multiple African sites6
and a concerning increase in antimicrobial resistance.7,8
The age profile for disease burden diers across dierent
epidemiological contexts.4
Various factors lead to underestimation of the true
incidence of disease, including the non-specific
presentation of the disease,9 the absence of accurate
point-of-care diagnostics,10 and the often indiscriminate
empirical use of antimicrobials for fever syndromes
without a specific diagnosis in endemic countries.11
Lancet Glob Health 2021;
9: e1688–96
*Contributed equally
†Contributed equally
Oxford Vaccine Group,
Department of Paediatrics,
University of Oxford, and the
NIHR Oxford Biomedical
Research Centre, Oxford, UK
(J E Meiring DPhil,
M Voysey DPhil, S Tonks BSc,
A J Pollard FMedSci); Malawi-
Liverpool-Wellcome Trust
Clinical Research Programme,
Blantyre, Malawi (J E Meiring,
D Thindwa MSc,
M A Gordon MD); Oxford
University Clinical Research
Unit, Patan Academy of Health
Sciences, Kathmandu, Nepal
(M Shakya MPH, S Dongol DPhil,
A Karkey DPhil,
B Basnyat FRCPE); Patan
Academy of Health Sciences,
Patan Hospital, Lalitpur, Nepal
(M Shakya, S Dongol, A Karkey);
International Centre for
Diarrhoeal Diseases Research,
Bangladesh, Dhaka,
Bangladesh (F Khanam MPhil,
K Zaman PhD, F Qadri PhD,
J Clemens MD); Department of
Epidemiology of Microbial
Diseases, Yale School of Public
Health, Yale University,
New Haven, CT, USA
(M T Phillips MS, V E Pitzer ScD);
College of Medicine, University
of Malawi, Blantyre, Malawi
(D Thindwa, M A Gordon);
Department of Infection,
Immunity and Cardiovascular
Disease, University of Sheffield,
Sheffield, UK
(T C Darton DPhil, J E Meiring);
Department of Medicine,
University of Cambridge,
Cambridge, UK (S Baker DPhil,
G Dougan DPhil); Nuffield
Department of Medicine,
Centre for Tropical Medicine
and Global Health, University
of Oxford, Oxford, UK
(C Dolecek MD, B Basnyat);
Mahidol Oxford Tropical
Medicine Research Unit,
Mahidol University, Bangkok,
Thailand (C Dolecek);

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The Peter Doherty Institute for
Infection and Immunity,
The University of Melbourne,
Melbourne, VIC, Australia
(S J Dunstan PhD); Department
of Infectious Diseases, Central
Clinical School, Monash
University, Melbourne, VIC,
Australia (K E Holt PhD);
Department of Infection
Biology, London School of
Hygiene & Tropical Medicine,
London, UK (K E Holt); National
Institute for Health Research
Global Health Research Unit on
Mucosal Pathogens, Division of
Infection and Immunity,
University College London,
London, UK
(R S Heyderman PhD); Institute
of Infection, Veterinary and
Ecological Sciences, University
of Liverpool, Liverpool, UK
(M A Gordon)
Correspondence to:
Dr James E Meiring, Department
of Infection, Immunity and
Cardiovascular Disease,
University of Sheffield,
Sheffield S10 2RX, UK
j.meiring@sheffield.ac.uk
Using data gaps identified through a typhoid trans-
mission model,12 the Strategic Typhoid Alliance across
Africa and Asia (STRATAA) consortium designed
a comprehensive study at three sites combining
household-level and individual-level demographic
census, health-care utilisation surveys, and enhanced
facility-based passive surveillance. Community-based
serological surveys were also done to further characterise
undiagnosed exposure to the bacteria. Here, we present
the overall and adjusted incidence of blood-culture-
confirmed S Typhi and S Paratyphi at three urban sites
in Africa (Blantyre, Malawi) and Asia (Kathmandu,
Nepal and Dhaka, Bangladesh) and seroconversion rates
for S Typhi.
Methods
Study design and site selection
The STRATAA programme is a prospective observational,
population-based collaborative and multidisciplinary
epidemiological study, comprising health-facility-based
passive surveillance for febrile illness, community-based
serological surveys, and health-care utilisation surveys
nested within a demographic house hold census (figure 1).
A detailed description of the study sites, design, and
methods (including sample size con siderations) has
been previously published.13
Briefly, the study was done in three urban areas
within the Ndirande township of Blantyre, Malawi,
the Lalitpur area of Kathmandu, Nepal, and Mirpur,
Dhaka, Bangladesh. Further information on the study
sites is provided in the appendix (p 1). Individuals who
were resident within households inside the demarcated
geographical area were eligible for inclusion in the
demographic census, with a household defined as
individuals living in the same dwelling or compound
and sharing food from the same kitchen. Approval for
the joint study protocol was obtained from local research
ethics committees at all participating centres and the
Oxford Tropical Research Ethics committee.
Demographic census, census update, and health-care
utilisation surveys
Within a demarcated geographical area, a baseline
census population was enumerated over a 3–5-month
period (June 1–Oct 18, 2016). Consent and demographic
infor mation were collected from the head of the
household. Each household and individual were given a
unique household and member identification number
and global positioning system (GPS) coordinates were
recorded. A census update was done three times in
Dhaka at intervals of 6 months and once in Kathmandu
at 1 year, and all three sites had a final census at 2 years.
Research in context
Evidence before this study
We considered evidence from a systematic review of typhoid
fever incidence studies published in February, 2017, in addition
to a PubMed search for articles done on Jan 1, 2021, using the
search terms “(typhoid OR Salmonella Typhi) AND
seroincidence”. Our search yielded 33 studies from sites in
21 countries that had reported on the incidence of blood-
culture-confirmed typhoid fever. No population-based
incidence studies of enteric fever have been done in Malawi or
Nepal. Two previous studies done in Dhaka, Bangladesh
reported typhoid fever incidence estimates of 395 cases per
100 000 person-years for the period 2000–01 and 280 cases
per 100 000 person-years for the period 2003–04. No previous
studies have estimated the seroincidence of infection with
Salmonella enterica serotype Typhi (S Typhi).
Added value of this study
We provide the first population-based enteric fever incidence
estimates for Blantyre, Malawi and Kathmandu, Nepal, and
updated estimates of incidence in Dhaka, Bangladesh. This is
also the first study to compare population-based estimates of
typhoid fever incidence with estimates of the seroincidence of
S Typhi infection on the basis of serial anti-Vi IgG titres.
We found a high incidence of typhoid fever, with overall crude
and adjusted incidence of blood-culture-confirmed S Typhi per
100 000 person-years of observation of 58 cases (95% CI
48–70) and 477 cases (95% credible interval [CrI] 372–770) in
Blantyre, 74 (95% CI 62–87) and 1065 (95% CrI 687–1824) in
Kathmandu, and 161 (95% CI 145–179) and 1138 (95% CrI
889–1477) in Dhaka, respectively. Seroconversion rates for
S Typhi infection per 100 000 person-years estimated from
anti-Vi seroconversion episodes in serological surveillance were
2505 (95% CI 1605–3727) in Blantyre, 7631 (95% CI
5913–9691) in Kathmandu, and 3256 (95% CI 2432–4270) in
Dhaka. Additionally, we found high rates of antimicrobial
resistance across the three sites, with multidrug resistance
identified in 44% of isolates and fluoroquinolone resistance
identified in 61% of isolates.
Implications of all the available evidence
The high burden of typhoid fever at these study sites provides
evidence to support decision making on typhoid conjugate
vaccine introduction in these countries. Paratyphoid fever is
rarely observed in sub-Saharan Africa, but accounts for
5–25% of enteric fever cases in south Asia. Antimicrobial
resistance is common among isolates of both S Typhi and
S enterica serotype Paratyphi A, but patterns of resistance vary
between sub-Saharan Africa and south Asia. Passive
surveillance of blood-culture-confirmed enteric fever cases
considerably underestimate the true incidence of the disease.
Seroincidence data can complement traditional population-
based surveillance of blood-culture-confirmed typhoid fever,
but further research is needed to interpret the significance of
increases in anti-Vi titres.
See Online for appendix

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All data were collected through Open Data Kit Collect
using Android-based tablet devices, and stored on a
MySQL database.14
Two health-care utilisation surveys were done at
each site between 2016 and 2018. Approximately
735 households with children were interviewed per
survey to estimate the probability that those with fever
would seek health care at a designated study facility
(appendix p 6). Households were selected randomly from
the demographic census.
Passive surveillance
Participants within the demographic census area were
encouraged to attend study health-care facilities for blood
culture and treatment if they developed fever. Participants
presenting from within the geographical census area
were approached for recruitment if they had a history of
fever for 72 h or more (later changed to ≥48 h) or current
temperature of 38·0°C or higher (appendix p 1).
Serosurveys
Approximately 8500 participants were randomly selected
in an age-stratified manner from the original demo-
graphic census (appendix p 7). Using GPS or address
data these individuals were followed up by field teams,
and paired samples of 1–3 mL of blood were collected
twice with a 3-month interval.
Microbiological culture of blood was done using
an automated system (BD BACTEC Blood Culture System
[Becton-Dickinson, Franklin Lakes, NJ, USA] or BacT/
ALERT [BioMerieux, Marcy-l’Étoile, France]) at all
three sites following collection of a single aerobic bottle.
For positive cultures exhibiting growth, organisms
were then identified using colony morphology, Gram
staining, standard biochemical tests, and specific antisera,
with particular focus on the identification of S Typhi,
S Paratyphi, and non-typhoidal salmonellae.15 Antimicrobial
susceptibility testing was done using the disc diusion
method as per the British Society for Antimicrobial
Figure 1: Dates and recruitment numbers for each component of the study
Census
Survey period
Survey period
Survey period
Households, n
Households, n
Population, n
Health-care
utilisation survey
Survey period
Passive surveillance
Facility type
Enrolled, n
Enrolled, n
S Typhi isolates, n
Salmonella enterica
serotype Paratyphi
isolates, n
Salmonella enterica
serotype Paratyphi
isolates, n
Serosurvey
Blantyre, Malawi
Baseline Final Baseline BaselineFinal FinalUpdate 1 Update 1 Update 2
Kathmandu, Nepal Dhaka, Bangladesh
July 4–
Oct 18, 2016
Aug 6, 2018–
April 23, 2019
June 2–
Aug 29, 2016
March 27–
July 27, 2017
May 22–
Aug 31, 2018
June 1–
Aug 31, 2016
March 18–
Aug 16, 2017
Oct 22, 2017–
Jan 11, 2018
June 7–
Sept 25, 2018
22
364
97
392
Health-care
utilisation
survey 1
April 1–
June 15, 2017
683
23
826
102
242
Health-care
utilisation
survey 2
May 1–
June 30, 2018
448
24
405
101
810
24
897
102
590
22
342
101
021
26
119
110
731
26
010
111
418
26
238
112
830
26
112
110
963
Health-care utilisation
survey 1
Dec 1–17, 2016
735
Health-care utilisation
survey 2
Aug 7–30, 2017
743
Health-care utilisation
survey 1
Nov 1–Dec 19, 2016
787
Health-care utilisation
survey 2
Sept 11–Oct 2, 2017
747
Nov 1, 2016–Oct 31, 2018
Inpatients: Queen Elizabeth
Central Hospital
Outpatients: Ndirande
Community Clinic
3594
115
0
16
Jan 10, 2017–July 28, 2018
Jan 1, 2017–Dec 31, 2018
Inpatients: Patan Hospital
Outpatients: Patan Hospital Adult and
Paediatric Outpatient Clinics
2473
150
13
0
Jan 1, 2017–Dec 31, 2018
Inpatients: Mirpur Field Clinic and Mirpur Treatment Centre
Outpatients: Adhunik Hospital, Dhaka Hospital,
Kalsi Shisu Hospital, Radda MCH-CP Centre, and Shaheed
Suhrawardy Medical College and Hospital
6015
359
95
0
Jan 24, 2017–Aug 31, 2018
7818
(outpatient
visit 1)
5092
(outpatient
visit 2)
6616
(outpatient
visit 1)
Feb 26, 2017–Feb 19, 2018
8282
(outpatient
visit 1)
4493 (outpatient visit 2) 7041 (outpatient visit 2)

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Chemotherapy16 or Clinical and Laboratory Standards
Institute17 guidelines; antibiotic discs used for the tests
were obtained from Oxoid (Basingstoke, UK). Further
details on quality control are included in the appendix
(p 2).
Anti-Vi IgG titres in plasma collected from participants
were measured using the commercial VaccZyme ELISA
kit (The Binding Site, Birmingham, UK) according to the
manufacturer’s guidelines.
Statistical analysis
We calculated crude incidence rates by dividing the
number of blood-culture-confirmed cases by the total
amount of person-time observed in each age group
and for the entire census population in each site;
and estimated 95% binomial CIs. To account for the
underestimation of typhoid fever incidence based on
culture-confirmed cases, we adjusted the observed crude
incidence rates of S Typhi for blood-culture sensitivity,
the probability of receiving a blood culture diagnostic
test, and the probability of health-care-seeking using a
Bayesian framework that incorporated both observed
STRATAA data and information from the literature.
Adjustments factors were site-specific and varied by age
group.18 We calculated median values and 95% Bayesian
credible intervals for the adjusted incidence estimates
(appendix p 2).
We defined seroconversion as a 2-fold increase in
anti-Vi IgG titres and an absolute titre of 50 EU/mL
or higher at the second timepoint to account for
small variations above the lower limit of detection; the
absolute titre threshold was based on baseline data
from presumably unexposed participants in a human
challenge model.19 We divided the number of participants
with an increase in antibody titre that met the definition
for seroconversion by the total person-time in each age
group, only including participants with two blood tests
done approximately 3 months apart. Person-time was
determined by multiplying the number of participants
in each age group by the mean time between visits
(in years) for the entire cohort to give an estimate of
seroincidence per 100 000 person-years of observation.
We estimated 95% binomial CIs.
Role of the funding source
The study funders had no role in study design, data
collection, data analysis, data interpretation, or writing of
the report.
Results
423 618 individuals residing in 99 033 households were
included in the demographic censuses, contributing
626 219 person-years of observation for febrile illness
surveillance (199 634 in Blantyre, 203 614 in Kathmandu,
222 971 in Dhaka; appendix p 7).
During the 2-year period of passive surveillance,
12 082 individuals who met the fever criteria (n=3594 in
Blantyre, Malawi Kathmandu, Nepal Dhaka, Bangladesh
S Typhi S Typhimurium Blood-culture
negative
S Typhi S Paratyphi A Blood-culture
negative
S Typhi S Paratyphi A Blood-culture
negative
Enrolled participants, n 115 16 3594 150 13 2230 359 95 4931
Number of enrolled patients with
available data
105 12 3594 150 13 2230 359 95 4931
Enrolment location
Community clinic 93/105 (89%) 11/12 (92%) 3385/3594 (94%) 148/150 (98%) 13/13 (100%) 2159/2230 (97%) 352/359 (98%) 95/95 (100%) 4894/4931 (99%)
Hospital 12/105 (11%) 1/12 (8%) 209/3594 (6%) 2/150 (2%) 0 71/2230 (3%) 7/359 (2%) 0 37/4931 (1%)
Participant characteristics
Sex
Men 53/105 (50%) 5/12 (42%) 1791/3594 (50%) 88/150 (59%) 8/13 (62%) 1262/2230 (57%) 185/359 (52%) 56/95 (59%) 2429/4931 (49%)
Women 52/105 (50%) 7/12 (58%) 1803/3594 (50%) 62/150 (41%) 5/13 (38%) 968/2230 (43%) 174/359 (48%) 39/95 (41%) 2502/4931 (51%)
Age, years 9·9 (6–17)* 1·6 (1·4–2·9)† 4 (2–10)‡ 12·9 (8·4–21·2)* 11·9 (8–24) 8·1 (3·7–20) 8·2 (4·8–16)* 12·4 (7·6–24·1) 12·4 (5–28)
Body temperature, °C 38·6 (38·1–39·1)* 38·3 (37·9–38·8) 38·2 (37·7–38·8) 38·3 (37–39)* 37·6 (36·9–38·2) 37·7 (36·7–38·5) 37·8 (37–38·5)* 37·8 (36·9–38·5) 37·2 (36·5–38·2)
Duration of fever, days 6 (3–7)* 3 (2·8–8·8) 3 (2–3) 4 (3–6)* 3 (3–5) 3 (3–5) 4 (4–7)* 5 (4–7) 4 (3–7)
Patients admitted to hospital 8/105 (8%) 2/12 (17%) NA 5/150 (3%) 0 NA 10/359 (3%) 1/95 (1%) NA
Duration of hospital stay, days NA NA NA 9·5 (8–10) NA NA 5·5 (3–7) 3 (3–3) NA
Deaths 2/105 (2%) 3/12 (19%) NA 0 0 NA 0 0 NA
Antibiotics in previous 2 weeks 28/105 (27%)* 5/12 (42%)† 281/3594 (8%) 47/150 (31%)* 3/13 (23%) 378/2230 (17%) 123/359 (34%)* 30 (32%) 774/4931 (16%)
Antibiotic prescribed at visit to
health-care facility or hospital
82/105 (78%)* 9/12 (75%)§ 2693/3594 (74%) 120/150 (80%) * 11/13 (85%)§ 1276/2230 (57%)‡ 337/359 (94%)* 88 (93%) 2117/4931 (43%)‡
Data are n, n/N (%), or median (IQR). No cases of blood-culture-confirmed S Paratyphi A were identified in Blantyre and no cases of blood-culture-confirmed S Typhimurium were identified in Kathmandu or Dhaka. S Typhi=Salmonella enterica serotype
Typhi. S Paratyphi=Salmonella enterica serotype Paratyphi. S Typhimurium=Salmonella enterica serovar Typhimurium. NA=not available. *S Typhi vs blood-culture negative, p<0·0001. †S Typhi vs S Paratyphi or S Typhimurium, p<0·0001. ‡S Paratyphi or
S Typhimurium vs blood-culture negative, p<0·05. §S Typhi vs S Paratyphi or S Typhimurium, p<0·05.
Table 1: Characteristics of enrolled participants

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Blantyre, n=2473 in Kathmandu, and n=6015 in Dhaka)
were enrolled from ten health-care facilities (two in
Blantyre, two in Kathmandu, and six in Dhaka). Baseline
characteristics for febrile patients are described in table 1.
Pathogenic bacteria were isolated from the blood
cultures of 822 (6·8%) of 12 082 participants: 162 (4·5%)
in Blantyre, 166 (6·9%) in Kathmandu, and 494 (9·2%) in
Dhaka. The most common bacteria were S Typhi
(624 [76·2%] of 822 isolates; 115 in Blantyre, 150 in
Kathmandu, and 359 in Dhaka), S Paratyphi A (108 isolates
[13·0%] of 822 isolates; 13 in Kathmandu, 95 in Dhaka),
and Salmonella enterica serovar Typhimurium
(S Typhimurium; 16 [1·9%] of 822 isolates in Blantyre).
Blood-culture positivity rates for typhoidal pathogens
(S Typhi and S Paratyphi A and B) were 3·2% in Blantyre,
6·6% in Kathmandu, and 8·2% in Dhaka. The overall
contamination rate was 7·9% (322 [9·0%] in Blantyre,
56 [2·3%] in Kathmandu, and 574 [9·5%] in Dhaka).
The incidence of hospital admission for typhoid fever
was higher in Blantyre (eight [7·9%] hospital admissions
among 105 cases) than in Kathmandu (five hospital
admissions [3·3%] among 150 cases) and Dhaka (ten
hospital admissions [2·5%] among 359 cases), and
deaths secondary to typhoid infection were only reported
in Blantyre (two deaths [1·9%] among 105 cases).
Previous antimicrobial usage and prescription of anti-
microbials following blood-culture collection was
significantly higher in blood-culture positive individuals
than blood-culture negative indi viduals across all three
sites (table 1).
The crude incidence of blood-culture-confirmed
S Typhi infection was 58 cases (95% CI 48–70) per 100 000
person-years of observation in Blantyre, 74 cases (62–87)
per 100 000 person-years of observation in Kathmandu,
and 161 cases (145–179) per 100 000 person-years of
observation in Dhaka (table 2). Age-stratified unadjusted
incidence for S Typhi was highest among individuals
aged 5–9 years at all three sites (table 2); in Dhaka, the
incidence rates for individuals aged 4 and 5 years
was higher than the other sites (643 cases [424–936] per
100 000 person-years of observation and 620 cases
[405–908] per 100 000 person-years of observation,
respectively; appendix p 11).
S Paratyphi was not identified in Blantyre; overall crude
incidence of blood-culture-confirmed S Paratyphi A
infection was 6 cases (95% CI 3–10) per 100 000 person-
years of observation in Kathmandu and 42 cases (34–52)
per 100 000 person-years of observation in Dhaka, with
the highest incidence identified among individuals aged
5–9-years.
In Blantyre, the incidence of Salmonella Typhimurium
(causing invasive non-typhoidal Salmonella disease)
was highest among individuals aged 2 years (124 cases
[45–269] per 100 000 person-years of observation;
appendix p 11). S Typhi was isolated from children
younger than 2 years at all sites (appendix p 11).
Blantyre, Malawi Kathmandu, Nepal Dhaka, Bangladesh
Crude incidence
(95% CI)
Adjusted incidence*
(95% CrI)
Incidence
ratio
(adjusted/
observed)
Crude incidence
(95% CI)
Adjusted incidence*
(95% CrI)
Incidence
ratio
(adjusted/
observed)
Crude incidence
(95% CI)
Adjusted incidence*
(95% CrI)
Incidence
ratio
(adjusted/
observed)
0–4 years 83 (53–124) 632 (398–965) 7·6 72 (33–136) 764 (307–1921) 10·7 417 (337–511) 2625 (1764–4244) 6·3
5–9 years 146 (103–201) 861 (599–1203) 5·9 341 (250–455) 6713 (3085–18 730) 19·7 554 (456–666) 3228 (2276–4757) 5·8
10–14 years 88 (56–132) 602 (377–915) 6·9 191 (128–275) 3750 (1653–10 559) 19·6 268 (203–348) 1564 (1050–2384) 5·8
15–29 years 32 (20–48) 361 (219–567) 11·4 92 (71–119) 1457 (684–3918) 15·8 98 (76–124) 956 (603–1635) 9·8
≥30 years 21 (10–37) 248 (124–447) 12·0 6 (2–13) 92 (29–301) 15·0 29 (19–42) 279 (157–514) 9·7
All ages 58 (48–70) 444 (347–717) 7·7 74 (62–87) 1062 (683–1839) 14·4 161 (145–179) 1135 (898–1480) 7·0
Rates are per 100 000 person-years of observation. CrI=credible interval. *Adjusted for blood-culture sensitivity, probability of receiving a blood culture diagnostic test, and probability of health-care seeking.
Table 2: Incidence of blood-culture-confirmed typhoid fever by site and age
0500 1000 1500 2000
Dhaka,
Bangladesh
Kathmandu,
Nepal
Blantyre,
Malawi
Incidence (per 100 000 person-years of observation)
444 (347–717)
314 (250–504)
109 (87–174)
58 (48–70)
1062 (683–1839)
162 (131–211)
135 (113–160)
74 (62–87)
1135 (898–1480)
311 (275–352)
298 (264–336)
161 (145–179)
Incidence estimates
per 100
000
person-years
(95% CrI)
Crude incidence
Adjusted for blood-culture sensitivity alone
Adjusted for blood-culture sensitivity and probability
of receiving a blood-culture diagnostic test
Adjusted for blood-culture sensitivity, probability of
receiving a blood culture diagnostic test, and health-care
seeking
Figure 2: Crude observed incidence and adjusted incidence of typhoid fever caused by
Salmonella enterica serotype Typhi across the three study sites
CrI=credible interval.

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The adjusted incidence of typhoid fever was highest
among individuals aged 5–9-years at all three sites (table 2,
figure 2). The largest adjustments at each site were
for the the probability of being enrolled and receiving a
blood culture in Blantyre (2·9-fold increase) and for the
probability of seeking health care in Kathmandu (6·7-fold
increase) and Dhaka (3·7-fold increase; table 2, figure 2).18
The antimicrobial susceptibility profiles for both S Typhi
and S Paratyphi A diered at each site (appendix p 9).
Fluoroquinolone non-susceptibility was common among
S Typhi isolates in Dhaka (355 [99%] of 359 isolates) and
Kathmandu (127 [83%] of 153 isolates), but was only
identified in a single isolate from Blantyre (one [<1%]
of 115 isolates). Fluoroquinolone non-susceptibility
was almost universal among S Paratyphi A isolates
(14 [100%] of 14 isolates in Kathmandu, 94 [>99%] of
95 isolates in Dhaka). In contrast, 92% of S Typhi isolates
from Blantyre were multidrug resistant (resistant to
ampicillin, chloram phenicol, and cotrimoxazole), whereas
only 1% of isolates in Kathmandu and 39% of isolates
in Dhaka were multidrug resistant. Azithromycin non-
susceptibility was detected in both Asian sites but was not
assessed in Blantyre. Azithromycin non-susceptibility was
more frequent in S Paratyphi A (four [30%] of 14 isolates
in Kathmandu, 41 [43%] of 95 isolates in Dhaka) than
S Typhi (ten [7%] of 150 isolates in Kathmandu,
11 [3%] of 359 isolates in Dhaka).
The seroconversion data showed dierent rates of
presumed exposure to and infection with S Typhi in the
three sites (figure 3; appendix p 15). Overall seroincidence
was highest in Kathmandu (7631 episodes [95% CI
5913–9691] per 100 000 person-years of observation), was
more than seven times higher than the estimated
adjusted incidence, and more than 100 times higher than
the observed blood-culture-confirmed incidence. The
seroincidence in Blantyre (2505 episodes [1605–3727] per
100 000 person-years of observation) was five times
higher than the adjusted incidence and 43 times higher
than the observed incidence, and the seroincidence in
Dhaka (3256 episodes [2432–4270] per 100 000 person-
years of observation) was 2·5 times higher than the
adjusted incidence and 20 times higher than the observed
incidence (figure 3).
Similar to the incidence estimates from passive
surveillance, the seroincidence analysis showed that
exposure was highest among the youngest age groups
(figure 3). The seroincidence estimates for Dhaka among
indiv iduals aged 0–4-years mirrored the passive
surveillance estimates in which incidence was highest
among individuals aged 4 years. At all sites, but
particularly in Kathmandu, high rates of seroconversion
were observed in the older age groups (age >30 years), in
contrast with the lower age-specific incidence rates
captured from passive surveillance.
Discussion
In this STRATAA surveillance study, S Typhi was the
primary cause of bacterial bloodstream infection in
people with fever across three dierent epidemiological
contexts in Africa and Asia. Crude incidence of blood-
culture-confirmed disease identified through passive
surveillance were adjusted to estimate the incidence of
typhoid fever occurring within the census populations
using parameters measured from within the populations,
indicating that true rates are likely to be considerably
higher than those estimated directly by blood culture.
Seroincidence data indicate that exposure to S Typhi
might be even higher, suggesting substantial numbers of
subclinical episodes, which might make an important
contribution to transmission in the population.12
In Dhaka, previous crude incidence estimates
from population-based studies have ranged from 200 to
390 cases per 100 000 person-years of observation20 for
all age groups, with the highest crude incidence rates
(of up to 1870 per 100 000 person-years of observation)
recorded in children younger than 5 years.21 The Global
Burden of Disease Study 2017 estimated an adjusted
incidence of 641 cases per 100 000 person-years of
observation in Bangladesh, reduced from 1459 per
100 000 person-years of observation in 1990.2 In this
study, the observed incidence (161 cases per
100 000 person-years of observation) and adjusted
incidence (1135 per 100 000 person-years of observation)
for all age groups were consistent with these previous
estimates and suggest that typhoid fever incidence
might not be declining as quickly as previously
estimated.2 Adjusted incidence of S Typhi was as high as
3228 cases per 100 000 person-years of observation in
the 5-9-year age group with the highest single-year
incidence among individuals aged 4 years.
Figure 3: Seroincidence estimates of Salmonella enterica serotype Typhi exposure
Seroincidence was calculated based on data from the serological survey, with randomly selected participants
sampled approximately 3 months apart. Seroconversion was defined as a 2-fold rise increase in anti-Vi IgG titres and
an absolute titre of 50 EU/mL or higher in the second sample at the second timepoint.
<5 years
5–9 years
10–14 years
15–29 years
≥30 years
All ages
0
5000
10
000
20
000
15
000
Seroincidence (per 100
000 person-years)
Age group
<5 years
5–9 years
10–14 years
15–29 years
≥30 years
All ages
Age group
<5 years
5–9 years
10–14 years
15–29 years
≥30 years
All ages
Age group
Blantyre, Malawi Kathmandu, Nepal Dhaka, Bangladesh

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A hospital-based study from Kathmandu estimated
overall crude S Typhi incidence to be 59 cases per
100 000 person-years of observation, averaged over a
4-year period, with a mean age of disease at 16 years.22
Although this estimate is similar to our observed
incidence of 74 cases per 100 000 person-years of
observation, our surveillance suggests that this is likely to
be a substantial underestimate, with adjusted incidence
of 1062 cases per 100 000 person-years of observation.
In Kathmandu, the proportion of participants using
alternative health-care facilities and private pharmacies
was high, particularly among the 5–9-year age group,
leading to a large increase in the adjusted incidence rate
when compared with the crude rate. Similar to estimates
for Dhaka, the highest observed and adjusted incidence
was observed among the 5–9-year age group; however,
these estimates also had the greatest degree of uncertainty
due to the infrequent use of study facilities.
Disease incidence estimates for Africa have
a greater level of uncertainty than estimates from Asia
due to fewer population-based studies. A meta-analysis
estimated adjusted rates of 620 cases per 100 000 person-
years of observation for eastern sub-Saharan Africa and
1459 cases per 100 000 person-years of observation for
central sub-Saharan Africa, although the estimates had
wide CIs.1 In Malawi, since 2010, an increase in the
number of S Typhi cases reported from central hospitals
has been observed, with a minimum adjusted incidence
estimate (accounting only for blood-culture sensitivity)
of 207 cases per 100 000 person-years of observation at
the peak of the typhoid fever outbreak in 2013 in
Blantyre.23 Our results detail the ongoing high incidence
of disease in Blantyre (adjusted incidence 444 cases per
100 000 person-years of observation).
The surveillance data were consistent with other
published data on the increasing importance of
S Paratyphi A in both Dhaka (117 cases per 100 000 person-
years of observation) and Kathmandu (37 cases per
100 000 person-years of observation)5,24 in the 5–9-year age
group. In Blantyre, no cases of S Paratyphi A were
identified, but consistent with surveillance across Africa,6
a considerable burden of S Typhimurium remains in
the youngest children (observed incidence 117 cases
per 100 000 person-years of observation among children
aged 2 years).
Salmonellae are on the WHO priority pathogen list due
to the high rate of associated antimicrobial resistance
and the risk this confers to human health.25 Data from
STRATAA surveillance are consistent with published
meta-analyses on the increase in antimicrobial resistance
among typhoidal Salmonellae and the dierent anti-
microbial resistance profiles of S Typhi and S Paratyphi A,
and dierences in antimicrobial resistance between Africa
and Asia.26 Isolates from Blantyre were almost entirely
multidrug resistant, with one case of fluoroquinolone
non-susceptibility documented during the surveillance
period. Since STRATAA was completed, additional isolates
with fluoroquinolone non-susceptibility have been
detected in Blantyre (unpublished data). By contrast, in
Dhaka and Kathmandu, high rates of fluoroquinolone
non-susceptibility and docu mented azithromycin non-
susceptibility were observed. These data, combined with
data from passive surveillance showing individuals who
were S Typhi culture positive had substantially higher
rates of antibiotic use before seeking health care and
higher rates of antibiotic prescription at the time of heath-
care facility visit, demonstrate the escalating risk of
antimicrobial resistance associated with global typhoid
management.
Our findings demonstrate that adjustment factors
cannot be applied universally to observed rates of blood-
culture-confirmed disease across dierent epidemio-
logical contexts and age groups. Use of alternative
health-care facilities and pharmacies was higher at Asian
sites than the African site, leading to higher inflation of
incidence once adjusted, whereas in Blantyre, fewer
individuals who sought health care at study facilities
received a blood culture due to high incidence of febrile
illness, inadequate health-care infrastructure, and
parental refusal.18
In Blantyre, individuals with typhoid presented with
more severe fever and a longer duration of fever, and
hospitalisation was two times higher than at the other
two sites. This dierence might indicate that despite
the adjustments for sampling and health-care seeking
behaviour, undetected mild or subclinical disease remains
an ongoing burden, consistent with the comparatively
high rates of seroconversion observed at the Blantyre site.
Such dierences might also reflect dierences in the
immunological history of individuals across the three
sites.
Measuring seroincidence, as described in this study,
provides an alternative estimate of the rate of exposure
to S Typhi than provided by passive blood-culture
surveillance. A cross-sectional seroepidemiological
study from Fiji estimated seroprevalence of anti-Vi IgG
antibodies to be higher than predicted based on blood-
culture-confirmed disease.27 A cross-sectional serological
study in Kathmandu showed that titres of anti-Vi IgG
were highest in the 16–55-year age group, consistent
with our data.28
This study is the first to use serological data to calculate
seroincidence for S Typhi across multiple sites. With the
exception of the 10–14-year age group in Dhaka, all the
age-specific seroincidence estimates either exceeded or
had overlapping CIs with the adjusted incidence esti-
mates from passive surveillance, such that seroincidence
could be used as an upper bound for disease incidence
within certain populations.
Quantifying the incidence of subclinical infections is
also key to understanding the contribution of dierent
age groups to the transmission of S Typhi. The high rates
of seroconversion among older individuals, particularly
in Nepal, could be evidence of ongoing exposure and

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transmission within these age groups, which due to the
high use of antimicrobials from community pharmacies,
or partial immunity leading to subclinical infection,
rarely requires hospital care.
A marked dierence was observed between the
seroincidence estimates and the adjusted incidence
estimates from passive surveillance across the three
sites, with higher seroincidence rates in Kathmandu
compared with Dhaka, in contrast to what was observed
in passive surveillance. No established cuto exists to
define seroconversion, and anti-Vi antibody might not be
the most accurate method of calculating seroincidence.
Further work examining dierent typhoid antigens
is ongoing.
This study has a number of limitations. First, due to the
very large number of individuals attending health-care
facilities, particularly in Blantyre, it was not possible to
enrol all eligible participants. Second, due to the high
number of private health-care facilities and pharmacies in
both Dhaka and Kathmandu, our surveillance sites only
captured a proportion of all febrile illnesses. Third, blood-
culture sensitivity is only around 60% and is aected by
previous antimicrobial use, volume of blood collected, and
timing of blood collection in the natural history of
infection. Sensitivity of blood culture is also aected by
the contamination rate at collection, which was higher in
Blantyre and Dhaka. Low sensitivity of blood culture is
likely to result in underestimation of incidence based on
blood-culture-confirmed cases, but we accounted for these
factors in the adjusted estimates. Fourth, to encourage
higher usage of study facilities, free treatment and care
was provided within the census populations by study
teams, to a variable extent at dierent sites. With improved
diagnosis through the use of blood culture and appropriate
prescription of antimicrobials, the hospital admission and
complication rate might have been falsely lowered
compared with other previously published observational
data.2,3,23 Fifth, during the surveillance period, a proportion
of the children from within these populations were
enrolled into a typhoid conjugate vaccine trial, which
might have introduced a degree of direct and indirect
protection to the communities.29 Individuals who were
eligible for vaccination in the trial were not included in the
seroincidence analysis, which reduced the numbers
of participants with paired samples, particularly in
Kathmandu. The use of anti-Vi IgG seroconversion as an
indicator of exposure to S Typhi infection is sensitive to
the thresholds used to define seroconversion, which are
based on scarce data. It is also possible that exposure to
non-typhoidal organisms (eg, Citrobacter) could elicit
these antibodies. Sixth, surveillance sites were chosen in
urban areas with known high enteric fever incidence, and
the geographical footprint and duration of surveil lance
was restricted. These factors together might reduce the
generalisability of these data to other sites.
Despite these limitations in the design of this
study, nesting multiple surveillance methods within a
demographic census allowed the weaknesses of individual
methods to be contextualised in dierent settings, and
varying populations to be characterised.
Our data support the WHO recommendation for
introduction of typhoid conjugate vaccines for children
from age 6 months. Catch-up campaigns are also likely to
be cost-eective,30 and should be implemented among
children up to age 15 years. Our seroincidence data also
suggest ongoing transmission into adulthood, which
would support the use of catch-up campaigns to reduce
transmission and the incidence of disease throughout
the entire population. Our data support modelling work
showing the impact vaccine catch-up campaigns could
have on local disease incidence.30 The introduction
of typhoid conjugate vaccines into these sites while
preventing disease and reducing the high incidence
identified through STRATAA, should also have an impact
on overall antimicrobial use and potentially rates of
resistance. High incidence of enteric fever necessitates
multiple intervention strategies to achieve global control
of these pathogens through development of water and
sanitation infrastructure, the introduction of ecacious
typhoid conjugate vaccines, and the development of
vaccines for S Paratyphi A.
Contributors
JEM, MS, and FK were responsible for the drafting of this Article.
JM, MTP, MV, and VEP led the data analysis and interpretation.
MAG, RSH, FQ, JC, BB, SB, and CD led the data collection at the three
sites represented within this report. ST, DT, TCD, SD, AK, KZ, SB, SD,
GD, KEH, MG, RSH, FQ, JC, BB, SB, CD, and AJP revised the report
critically. All authors have read and approved the final version of this
report. The corresponding author had full access to all the data in the study
and had final responsibility for the decision to submit for publication.
Declaration of interests
VEP is a member of the WHO Immunization and Vaccine-related
Implementation Research Advisory Committee. AJP chairs the
UK Department of Health Joint Committee on Vaccination and
Immunisation (JCVI) and is a member of the WHO Strategic Advisory
Group of Experts. RSH is supported by the National Institute for
Health Research (NIHR) Global Health Research Unit on Mucosal
Pathogens using UK aid from the UK Government. The views
expressed in this publication are those of the authors and not
necessarily those of the UK Department of Health, JCVI, WHO,
NIHR, or the Department of Health and Social Care. All other authors
declare no competing interests.
Data sharing
Deidentified individual participant data and a data dictionary can be
made available for passive surveillance, health-care utilisation, census,
and census update data on request to the chief investigator (andrew.
pollard@paediatrics.ox.ac.uk) with a research proposal and signed data
usage agreement. A study protocol and statistical analysis plan have
been published previously.13
Acknowledgments
This study was funded by a Wellcome Trust Strategic Award
(106158/Z/14/Z) and the Bill & Melinda Gates Foundation (OPP1141321).
We acknowledge the contribution of all participants who have taken part
in the studies and the large field and laboratory teams at the sites,
including: Amit Aryja, Binod Lal Bajracharya, David Banda,
Yama Mujadidi, Pallavi Gurung, Arifuzzaman Khan, Clemens Masesa,
Tikhala Makhaza Jere, Archana Maharjan, George Mangulenji,
Maurice Mbewe, Harrison Msuku, Nirod Chandra Saha,
Prasanta Kumar Biswas, Anup Adhikari, and the Nepal Family
Development Foundation team.

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